Segmentation research of pulmonary parenchyma based on improved convex hull algorithm

Accurate segmentation of pulmonary parenchyma has been one important research content of the computer-aided diagnosis of lung disease. Pulmonary parenchyma area with lesions cannot be divided by most of the traditional method of segmentation, and a great impact is brought for the image analysis and computer-aided decision. Thus, a lung parenchyma segmentation algorithm was proposed for lung CT image with edge-type pulmonary nodules. The algorithm is easy to implement and has a better experimental results. Firstly, we used conventional method to extract the rough contour of pulmonary parenchyma. Secondly, in connection with the absence of lung parenchyma lesions in the previous step, an improved two-dimensional convex hull algorithm was proposed to repair the pulmonary parenchyma contour. Finally, the pulmonary parenchyma internal contour was acquired by using regional growth and morphology comprehensively. The test results of the experiment on 200 clinical chest CT images showed that: compared with the existing ball pivoting algorithm and convex hull algorithm to repair the lung parenchyma, the algorithm proposed in this paper has higher accuracy. The accuracy rate can reach 90% or more. Lesions like borderline pulmonary nodules can be represented exactly and it is the basics of establishing the efficient pulmonary disease diagnosis system.